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Can Artificial Intelligence Help MSPs Increase Their Bottom Line?

Artificial intelligence (AI) is the latest tech buzzword and voice technology is nothing new, but together, both are changing the way people live. Consumers can now shop for groceries and complete other routine tasks from the comfort of their own home thanks to simple voice commands on AI-enabled virtual assistants. Adding to that, multiple research organizations predict that businesses could see improvements in productivity and profitability in the years to come just from weaving AI into their operations. A study by Accenture revealed that AI has the potential to boost profitability by 38 percent across 16 different industries by 2035.

AI and machine learning (ML) have become the talk of the IT service management (ITSM) industry as well. Vendors have started implementing ML algorithms in their ITSM tools — including their solutions for managed service providers (MSPs) — for functions like automatically categorizing tickets, predicting anomalies, and suggesting solutions for user issues. And with the advances made in technology each day, AI and ML could soon do a lot more than just these functions.

So, what could AI mean for MSPs? Could it help them in two key areas: service delivery excellence and profitability? To answer this, one needs to understand how AI technologies, including ML and natural language processing, are poised to take over a few major functions in the IT service delivery process.

Aiding technicians with decision-making and fine-tuning ITSM processes

AI could improve various ITSM processes by introducing new functionalities and enhancing existing features, including:

  • Service request management: Auto-approvals and custom workflows for service requests to improve the quality of service delivery.
  • Incident and problem management: Proactive problem prediction and prevention to reduce service disruptions and the number of repeat incidents.
  • SLA management: Flagging requests that could violate SLAs based on knowledge gained from mining historic data.
  • Change management: Real-time and dynamic change workflows for risk-free change implementations.
  • Asset management: Intelligent asset life cycle management to reduce outages due to poor asset performance.

All of these applications of AI in ITSM can help increase the efficiency of IT service desk teams so workers can focus on other aspects of their jobs.

Intelligently handling it requests and incidents through virtual assistants

AI could slowly diminish the need for physical service desk teams. As time goes by, AI-driven virtual support agents could potentially replace the conventional IT service desk — the single physical point of contact between IT staff and end users. It might not happen soon, but it’s not difficult to imagine end users resetting a malfunctioning router or getting software installed through virtual assistants like Siri and Alexa. ITSM tool vendors may even develop proprietary AI-based virtual assistants that could perform these IT tasks. With virtual assistants already integrated into many services like weather updates and personal calendars, it won’t be long before these assistants start integrating with IT service desks, becoming the first and single point of contact for organizations’ end users.

Remember the days of IT service desk coordinators? When the process of categorizing, prioritizing and assigning tickets was done manually, with a help desk administrator employed just for this purpose? Thanks to ITSM automation, the need for a dedicated resource to do these tasks has diminished. Similarly, with intelligent virtual IT assistants taking care of activities like L1 tickets, IT firefighting and other regular IT chores, MSPs can deploy their technicians on activities that positively impact business, such as planning and executing IT strategies for their clients and digitally transforming their clients’ businesses.

AI and IT management

The data mining capabilities of ML-based models can also help MSPs improve other aspects of their IT management, such as:

  • Endpoint management: Automatically determine the best time to push patches to each endpoint, which greatly reduces failures and increases client satisfaction.
  • Security information event management: Enable intelligent detection of data exfiltration and identify root causes for repeated account lockouts and user logon failures.
  • IT operations: Receive intelligent recommendations for the best times to perform firmware upgrades, and follow AI predictions to control errors in configuration changes and prevent downtime.

All of the AI technologies mentioned above could boost the productivity of MSPs, saving several hundred man-hours every month. Better productivity could also translate into higher returns for both AI investments and human resource investments — and improve an MSPs’ bottom line.

This article was originally published on XaaS Journal